That's one of the core high-level AI debates going back decades, whether a fundamentally different hardware substrate is needed for intelligent machines, or if

That's one of the core high-level AI debates going back decades, whether a fundamentally different hardware substrate is needed for intelligent machines, or if it's instead more of a 'software' problem. Biologically-inspired AI tends to want to build things that look more like networks of neurons as the hardware substrate (among other things), while some other branches of AI find existing computing hardware to be generally fine as a substrate. Imo it comes down to more of a pragmatic question than a philosophical one, though. Unless we actually discover a super-Turing computational system, any machine will be doing some kind of computation that in principle could be performed by any other Turing-equivalent machine. Of course not all Turing-equivalent machines are equally easy to build everything on top of, which is where the "equivalent in principle" part falls short. But alternate hardware models (assuming not super-Turing ones) don't in themselves get you anything that in some inherent or philosophical sense can't be done by a pile of NAND gates.